Function TEST

tensorflow/core/kernels/tensor_flag_utils_test.cc:38–132

using tensorflow::tensor_flag_utils::ValidateSparseMatrixShardingConfig;

TEST(SparseUtilsTest, ValidateSparseMatrixShardingConfig) {
  // Only a default is specified.
  {
    Tensor t(DataType::DT_FLOAT, {});
    t.scalar<float>()() = 0.7;
    EXPECT_TRUE(ValidateSparseMatrixShardingConfig(t).ok());
  }
  {
    Tensor t(DataType::DT_FLOAT, {});
    t.scalar<float>()() = 1.0;
    EXPECT_TRUE(ValidateSparseMatrixShardingConfig(t).ok());
  }

  // Misshapen.
  {
    Tensor t(DataType::DT_FLOAT, {1, 1});
    int indx = 0;
    for (const float v : {60.0}) {
      t.flat<float>()(indx++) = v;
    }
    EXPECT_EQ(INVALID_ARGUMENT, ValidateSparseMatrixShardingConfig(t).code());
  }
  {
    Tensor t(DataType::DT_FLOAT, {1, 2});
    int indx = 0;
    for (const float v : {
             60.0,
             50.0,
         }) {
      t.flat<float>()(indx++) = v;
    }
    EXPECT_EQ(INVALID_ARGUMENT, ValidateSparseMatrixShardingConfig(t).code());
  }

  // Only one key is specified.
  {
    Tensor t(DataType::DT_FLOAT, {1, 3});
    int indx = 0;
    for (const float v : {30.0, 20.0, 1.0}) {
      t.flat<float>()(indx++) = v;
    }
    EXPECT_TRUE(ValidateSparseMatrixShardingConfig(t).ok());
  }

  // Two keys are specified.
  {
    Tensor t(DataType::DT_FLOAT, {2, 3});
    int indx = 0;
    for (const float v : {60.0, 50.0, 0.41, 30.0, 20.0, 0.7}) {
      t.flat<float>()(indx++) = v;
    }
    EXPECT_TRUE(ValidateSparseMatrixShardingConfig(t).ok());
  }

  // Out of range.
  {
    Tensor t(DataType::DT_FLOAT, {2, 3});
    int indx = 0;